BJS01 Propensity score analysis of prognostic benefit of prehabilitation in Upper Gastro-Intestinal cancer surgery
Bibliographic record
Abstract
Abstract Background Risk profile assessment by prehabilitation (prehab) is an important emerging policy in patients with suspected cancer. This study aimed to determine the value of prehab at index consultation in Upper Gastro-Intestinal (UGI) cancer with the hypothesis that prehab would improve outcomes. Methods Consecutive 907 patients were studied prospectively (182 receiving prehab) and outcomes were compared with historical controls, incorporating a propensity score analysis. Primary outcomes were operative morbidity, mortality, Length of Hospital Stay (LoHS), clinical effectiveness related to Quality-Adjusted Life Years (QALYs) to price a treatment’s cost-effectiveness and Overall Survival (OS). Results After regression for confounding factors, a cohort of 907 patients was available, with 182 receiving prehab (median age 67 y, 128 Oesophageal (OC), 54 Gastric Cancer (GC)) and 725 control therapy [67 y, 410 OC, 315 GC]. Prehab operative morbidity (Clavien-Dindo ³ 3) and mortality were 18.1 and 1.6% vs. 20.4 (p=0.215) and 2.5% (p=0.484) in controls and median LoHS 11 vs. 13 days (p=0.007). Two-year OS after prehab was 67.9 vs. 59.1% in controls (p=0.027). Multivariable analysis revealed that prehab (HR 0.647, p=0.026), positive resection margin (HR 1.345, p=0.036), peri-operative Acute Kidney Injury (HR 2.645, p<0.001) and pTNM stage; stage II (HR 2.159, p=0.037), stage III (HR 4.234, p<0.001) and stage IV (HR 5.892, p<0.001), were associated with OS. The cost per QALY for OC was £8,851 and GC £7,614. Conclusion Prehab was associated with two-day shorter LoHS and 9% better OS, supporting the hypothesis that prehab is an important cost-effective strategy related to NICE guidance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".